The expression of miR-30a* and miR-30e* is associated with a dualistic model for grading ovarian papillary serious carcinoma

  • Authors:
    • Yan Wang
    • Lv Li
    • Zhenyun Qu
    • Ruomeng Li
    • Tie Bi
    • Jiyong Jiang
    • Henan Zhao
  • View Affiliations

  • Published online on: March 27, 2014     https://doi.org/10.3892/ijo.2014.2359
  • Pages: 1904-1914
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Abstract

Histological grade has already been recognized as a very important prognostic factor for ovarian papillary serous carcinoma (OPSC). On the basis of pathogenetic mechanisms, recent findings suggest a dualistic model of OPSC consisting of types I (low-grade) and II (high-grade) cancers. High-grade OPSC is responsible for most ovarian cancer deaths. The goal of our investigation was to identify the differences in key miRNAs and possible regulators through miRNA microarray chip analysis, as well as functional target prediction and clinical outcome between the low and high-grade OPSC patients. The pathogenic basis in differentiation of ovarian cancer subtypes was studied to provide insight into diagnosis and therapy for high-grade cases. Through microarray analysis, we found that miR-30a* and miR-30e* were the top 2 significantly different miRNAs between type I and type II OPSC patients, and both were remarkably downregulated in the latter type. ATF3 and MYC were indicated as potential co-targets of miR-30a* and miR-30e*, and showed a significant upregulation in type II patients. As ATF3 and MYC are often associated with aggressive behavior and poor differentiation, especially in human cancers, these results are in good agreement with our findings and point toward a regulating differentiation function of the miR-30a* and miR-30e* genes. Further analysis using leave‑one-out cross predictions and Kaplan-Meier survival analysis strongly suggested that miR-30a* and miR-30e* can be used as biomarkers to tailor histological grade before starting the regimen, and they showed important roles in ovarian cancer differentiation resulting in poorer prognosis. In general, miR-30a* and miR-30e* coupled with expression data that reveal pathogenic regulation to predict histological differentiation, may operate to direct the formation of early detection and therapeutic approaches to individual OPSC patients, especially differentiation therapy to high-grade cases.

Introduction

Ovarian cancer (OVC) is the most lethal gynecological malignancy and ovarian papillary serous carcinoma (OPSC) is the largest histology subgroup of ovarian cancer (14). Growing clinical evidence suggests that histologic grade has been determined to be an important prognostic factor for ovarian serous carcinoma (5,6). Traditionally, ovarian cancer has been graded as well, moderately and poorly differentiated. But based on recent molecular genetic studies with clinical and histopathologic findings, it was proposed that OPSC tumors can be grouped into a new dualistic model based on their distinct pathogenesis (68). In this model, all ovarian surface epithelial tumors are divided into two groups designated type I and II. Type I tumors are mainly low-grade and have low levels of chromosomal instability. In contrast, type II tumors are generally high grade with rapidly growing, high aggressiveness and almost always have progressed to advanced stage at diagnosis, where current available therapies are seldom effective (7,9). High-grade OPSC constitutes approximately 75% of ovarian cancer but is responsible for 90% of ovarian cancer deaths (7). This has important clinical implications as evidenced by the lack of sensitivity of type II tumors to the standard cytotoxic chemotherapy that is effective for high-grade serous carcinomas (1,6,10,11). Research is urgently needed on type II tumors to better recognize the cytogenetic aberrations of this disease and design more rational approaches to early detection and targeted therapies of this type of patients.

MicroRNAs (miRNAs) are short non-coding RNA molecules of 22–24 nucleotides that play important roles by affecting various pathways related to cancer progress such as cell cycle control, apoptosis, proliferation, differentiation, metabolism and migration (12,13). As a benefit from the advances in use of miRNA microarray technologies, we can apply this approach to identify the unique miRNAs in process of diseases. Our aim was to identify the differences of key miRNAs and possible regulators through miRNA microarray chip, functional target prediction, and clinical outcome between the low and high-grade OPSC patients to find the pathogenic basis in differentiation of ovarian cancer subtypes, and to provide insight into clinical diagnosis and therapy for high-grade cases.

Materials and methods

Patient and samples

Patients, who were surgically treated for ovarian cancer at the Obstetrics and Gynecology Hospital, Dalian, China between August, 2006 and November, 2010 were identified. Corresponding 69 OPSC samples (type I=16; type II=53) that were resected at the time of primary surgery from the patients were evaluated. All pathological specimens were reviewed by two independent pathologists with no knowledge of patients’ clinical data. The diagnosis of the cases was based on criteria of the International Federation of Gynecology and Obstetrics (FIGO) staging, and the grade was assigned according to the University of Texas M.D. Anderson Cancer Center (MDACC) grading system (5). The MDACC system is based primarily on the assessment of nuclear atypia (nuclear uniformity vs. pleomorphism) in the worst area of the tumor (5). Low-grade serous carcinoma is characterized as the absence of marked variation of size and shape, and their nuclei are uniformly oval or round with even or slightly irregular chromatin (Fig. 1A and B). On the contrary, the nuclei of high-grade serous carcinoma have marked variation in size (≥3:1) and shape and a very irregular chromatin pattern (Fig. 1C and D) (5). Only serous papillary histology was included in this investigation.

miRNA microarray and data analysis

A microarray platform optimized for the analysis of a panel of 768 human miRNAs was used to analyze and compare the pattern of miRNA expression between type I (n=8) and type II (n=5) OPSC. Total RNA that was enriched for miRNAs was extracted from the FFPE tissue by using the Ambion mirVana microRNA isolation kit (Ambion, Austin, TX, USA). The quality of total RNA was assessed using the Agilent Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Individual real-time quantitative polymerase chain reaction assays were formatted into a TaqMan low-density array (TLDA; Applied Biosystems, Foster City, CA, USA), which was performed at the Shannon McCormack Advanced Molecular Diagnostics Laboratory Research Services, Dana Farber Cancer Institute, Harvard Clinic and Translational Science Center. The normalized microarray data were managed and analyzed by Statminer version 3.0 (Integromics™, Waunakee, WI, USA).

RNA isolation and quantitative PCR

Total RNA was prepared using TRIzol reagent, following manufacturer’s instructions. Quantitative Real-Time PCR (qRT-PCR) was performed using the TaqMan MicroRNA Reverse Transcription Kit (Applied Biosystems) with ABI miRNA specific primers and primer kits on an Agilent Technologies Stratagent M×3000P (Agilent Technologies). Specific kits used were as follows: Hsa-miR-30a*: ABI#4373062; Hsa-miR-30e*: ABI#4427975. The products were detected with SYBR-Green I, and U6 small nuclear RNA as the endogenous control.

miRNA target prediction and pathway analysis

Currently, more than 900 human miRNAs are registered in the Sanger miRBase, and hundreds of potential targets are known for each miRNA. Several computational approaches were used to analyze target prediction of miRNAs, including Ingenuity Systems (Redwood City, CA, USA), MicroCosm Targets version 5 (http://www.ebi.ac.uk/enright-srv/microcosm/htdocs/targets/v5/), and miRBase (http://www.mirbase.org/). Functional analysis of these predicted targets was performed to identify biologic pathways, according to significant gene expression. In order to retrieve only the most relevant targets, and based on our previous study (4), we only listed the top 10 genes targeted by the miRNAs that showed the greatest differential expression in the patients between type I and II OPSC.

Semiquantitative reverse transcriptase PCR

The procedures for reverse transcription-polymerase chain reaction (RT-PCR) have been well established (1416). For semiquantitative 1-step RT-PCR analysis for ATF3 and MYC, 1 μg of total RNA was used as the template in RT-PCR with the forward and reverse primers of vinculin in the kit (Takara, Dalian, China) with the following program: RT at 30°C for 10 min, 42°C for 1 h, 99°C for 5 min, and 5°C for 5 min; PCR at 94°C for 2 min, followed by 33 cycles of amplification (94°C for 1 min, 48°C for 45 sec, and 72°C for 1 min), and by extension at 72°C for 7 min. The primers for the target and housekeeping genes (GAPDH) are summarized in Table I. After amplification, the samples were separated on 2% agarose gel, visualized and quantified by Labworks-Analyst (GeneCo) software.

Table I.

PCR primers used in this study.

Table I.

PCR primers used in this study.

Sequence (5’→3’)Calculated size of PCR primer product (bp)
ATF3Sense GCTAAGCAGTCGTGGTATGGG227
Antisense TCCTGGAGTTGAGGCAAAGAT
MYCSense CCACCCATGGCAAATTCCATGGCA602
Antisense TCTAGACGGCAGGTCAGGTCCACC
GAPDHSense TGCTGCCAAGAGGGTCAAG1,318
Antisense GCCTCCAAGACGTTGTGAGT
Immunohistochemistry (IHC)

The IHC staining procedure was described previously (4). Briefly, the sections were incubated in 3% H2O2 for 30 min to suppress endogenous peroxidase activity after dewaxing, and then further blocked with a mixed solution [10% goat serum and 3% Albumin Bovine (BSA) in PBS] for 1 h and incubated with the primary antibodies of ATF3 (1:100 dilution; Bioworld, cat. no. BS1245); or MYC (1:100 dilution; Bioworld, cat. no. BS2261) overnight at 4°C. On the second day, these sections were incubated with streptavidin-peroxidase according to the manufacturer’s instructions of the staining kit (Zhongshan Goldenbridge Biotechnology Company, Beijing, China), then, 3,3’-diaminobenzidine (DAB) staining was performed. For negative controls, the conditions and the procedures were the same except that primary antibody was eliminated.

Western blot analysis

Western blot analysis was performed as previously described (14). Harvested cells were lysed in lysis buffer (Beyotime Institute of Biotechnology, Shanghai, China), and the proteins (20 μg) were separated on 10% SDS-PAGE gels and transferred to nitrocellulose membranes. Membranes were blocked in PBS containing 0.05% Tween-20 (TBST) 5% non-fat milk and incubated with the following antibodies: rabbit anti-ATF3, rabbit anti-MYC and anti-GAPDH (Santa Cruz Biotechnology, Santa Cruz, CA, USA). After secondary antibody incubation, the signal analysis was performed by exposure of the blots to film, which was then scanned and band intensities were measured with Labworks-Analyst (GeneCo) software.

Statistical analysis

The results were analyzed by SPSS 17.0 (Chicago, IL, USA). Data are expressed as arithmetic means ± SD of the number (n) of experiments. Samples were analyzed with repeated measures analysis of variance, and differences in the incidences were analyzed using ANOVA. The overall survival duration was defined as the interval (in months) between the date of initial cytoreductive surgery to date of last follow-up or death. The survival time courses were studied using the Kaplan-Meier method, and groups were compared using the log-rank test; p<0.05 was considered statistically significant.

Results

Patient characteristics

The clinicopathological characteristics of the patients who contributed to the OPSC samples are listed in Table II. Sixty-nine patients were identified to fit the study criteria, including 16 type I and 53 type II OPSC patients. The percentage of patients with advanced stage (stages III and IV) disease and the presence of positive lymph nodes were all significantly higher in patients with type II OPSC compared with patients with type I OPSC (p<0.001 for all).

Table II.

Clinicopathological characteristics of the patients.

Table II.

Clinicopathological characteristics of the patients.

CharacteristicsOPSC patients (n=69)
p-valueb
Type I grade a (n=16)Type II gradea (n=53)
No. (%)No. (%)
Age at diagnosis
  Median48.259.90.041
  Range(21–74)(25–69)
FIGO stage at diagnosis<0.001c
  Stage II7 (43.8)3 (5.7)
  Stage III8 (50.0)37 (69.8)
    Stage IIIB5 (31.3)16 (30.2)
    Stage IIIC3 (18.8)21 (39.6)
  Stage IV1 (6.3)13 (24.5)
Lymphadenectomy
  Yes11 (68.8)43 (81.1)
  No4 (25.0)8 (15.1)
  Unknown1 (6.3)2 (3.8)
  Median no. nodes resected1118
  Presence of positive nodes<0.001
    Yes16 (20.3)212 (65.2)
    No52 (65.8)103 (31.7)
    Unknown11 (13.9)10 (3.1)

{ label (or @symbol) needed for fn[@id='tfn1-ijo-44-06-1904'] } FIGO, International Federation of Obstetrics and Gynecology.

a Grade according to the American Joint Committee on Cancer (AJCC) of ovarian cancer.

b Difference between groups calculated by AVON test for age and X2 test for all others.

c FIGO stage according to early stage (stage I and II) and advanced stage (stage III and IV) in type I grade and type II grade OPSC patients.

Analysis of microarray data

To further characterize the unique miRNAs in OPSC differentiation, specimens from the type I and type II grade OPSC patients were initially analyzed by miRNA microarray respectively. Of the 768 miRNAs analyzed by microarray, we found that 23 were significantly different (p<0.01 for all), with at least a 2-fold (p<0.05) change between type I and type II OPSC patients (n=8 and n=5 for the above group, respectively). The upregulation of 18 (78.3%) of these 23 key miRNAs was observed in the type I samples and 5 (21.7%) in the type II specimens (Fig. 2A and Table III). Importantly, 8 of the 18 miRNAs with distinctly statistical significance (p<0.001) were lowly expressed in the type II patients. In particular, miR-30a* and miR-30e* were the top 2 miRNAs that showed significant differential expression in OPSC patients between the type I and type II groups and were remarkably downregulated in the type II OPSC patients (p=7.83×10−06, 3.52 ×10−05 and adjusted p-value = 5.63×10−04, 1.08×10−04, respectively; Fig. 2A and Table III).

Table III.

Analysis of microRNA microarray data and qRT-PCR expression of selected miRNAs.

Table III.

Analysis of microRNA microarray data and qRT-PCR expression of selected miRNAs.

miRNA IDMicroarray (type I vs. type II)
qRT-PCRa
−ΔΔCtp-valueAdj.p-value (q)Type I gradeType II grade
Upregulated miRNAs
hsa-miR-188-3p4.7432108549.61E-034.66E-02
hsa-miR-220c5.7208806677.25E-033.95E-02
hsa-miR-30a*15.862476188 3.82E-05 4.36E-0319.29 (10.01–23.88)7.74 (2.05–15.75)
hsa-miR-30e*14.073272271 1.44E-05 1.06E-0315.86 (6.48–22.42)5.62 (1.58–11.61)
hsa-miR-3253.0300994792.58E-049.88E-03
hsa-miR-3261.7460443549.25E-034.59E-02
hsa-miR-409-5p7.8273168548.47E-034.33E-02
hsa-miR-516b2.8842688542.95E-049.95E-03
hsa-miR-518a11.8715879389.38E-034.59E-02
hsa-miR-518c3.821164199.32E-034.59E-02
hsa-miR-5442.9179801045.31E-033.16E-02
hsa-miR-548a-5p5.1145131884.83E-033.05E-02
hsa-miR-548b-3p4.0697148548.38E-034.32E-02
hsa-miR-556-3p6.0565588545.32E-044.36E-03
hsa-miR-628-3p4.9131045215.66E-048.78E-03
hsa-miR-875-3p2.2748458968.06E-045.05E-03
hsa-miR-885-3p3.2574003965.23E-041.36E-02
hsa-miR-9*7.5103128542.86E-032.01E-02
Downregulated miRNAs
hsa-miR-133b−1.9755046885.97E-033.39E-02
hsa-miR-220b−1.8025153541.24E-031.41E-02
hsa-miR-346−2.917470813 8.53E-05 6.73E-03
hsa-miR-525-5p−4.1570914385.18E-041.36E-02
hsa-miR-892a−2.1223437711.57E-031.41E-02

{ label (or @symbol) needed for fn[@id='tfn5-ijo-44-06-1904'] } The assay found that 23 miRNAs were statistically different (p<0.01) between the groups, with 18 (78.3%) miRNAs higher in the type I group and 5 miRNAs (21.7%) higher in the type II group. Three miRNAs exhibited even greater statistical significance (p<0.0001 and q-value<0.01) and of those, two were higher in the type I grade group and one was higher in the type II grade group. miR-30a* and miR-30e* were the top differential miRNAs of them (expression ratio of type I to type II = 15.86 and 14.07; p=3.82E-05 and 1.44E-05; adjust p-value = 4.36E-03 and 1.06E-03, respectively.

a qRT-PCR validation only for microarray results of miR-30a* and miR-30e*. P-value and adj.p-value with boldface mean their corresponding miRNA has top obvious significance in their group.

qPCR validation for microarray results

miR-30a* and miR-30e* were significantly downregulated in the type II OPSC when compared with the type I OPSC by using microarray analysis. In order to confirm microarray results, qRT-PCR validation was performed. RNA was isolated from a new set of FFPE tissues to increase the likelihood that the observed differences in miRNA expression profiles represent biologically significant changes. In keeping with microarray results, miR-30a* and miR-30e* were all lowly expressed in type II grade OPSC with significance, and representative analyses are shown in Fig. 2B and Table III.

Unique miRNAs and their co-target prediction

The analysis of miRNA predicted targets was determined using several computational approaches, including Ingenuity Systems, MicroCosm Targets version 5, and miRBase. Functional analysis of these predicted gene targets can help us to identify biologic pathways with significant involvement in gene expression. In order to retrieve only the most relevant targets, we listed only genes targeted by miR-30a* and miR-30e* that were remarkably downregulated in the type II vs. type I OPSC patients, and we found they have some targets in common suggesting that they might play important roles in pathogenesis in differentiation of ovarian papillary serous carcinoma. ATF3 and MYC were indicated as potential co-targets of both miRNAs (Fig. 3A).

Validation of miRNA target gene predictions

Although hundreds of targets for each miRNA were predicted using computational analysis of microarray data, the specific binding targets that directly correlated to key miRNA should be fully validated with standard approaches such as polymerase chain reaction (RT-PCR), western blot analysis or immunohistochemical assay. In target prediction analysis, ATF3 and MYC were predicted as potential co-targets of miR-30a* and miR-30e* (Fig. 3A), and present as regulators in the different pathways, which include tumorigenesis in numerous human cancers. RT-PCR analysis for ATF3 and MYC mRNA showed a significant upregulation in type II OPSC patients compared to type I cases (p<0.001 for all, Fig. 3B and C). These target gene predictions were all confirmed by western blot analysis results (p-value <0.001 and = 0.0028 for ATF3 and MYC respectively, Fig. 3B and C).

Immunohistochemical assay for the ATF3 and MYC proteins showed a relevant upregulation in type II OPSC cells compared to type I OPSC cells (Fig. 4). It is clear that these co-targets were all extensively distributed in the cytoplasm of cancer cells in the tissue of type II OPSC samples comparing with the type I OPSC sections (Fig. 4A). Through analysis with Image-Pro plus vision 6.0, positive area and Integrate Optical Density (IOD) per vision-field of ×400 immunohistochemistry images were detected. These results also support the conclusions of the immunohistochemical assay (Fig. 4B–C).

Prediction of histological grade and survival rate in OPSC patients using miR-30a* and miR-30e* expression patterns

To understand the significance of miR-30a*and miR-30e* expression patterns in epithelial ovarian cancer (EOC) differentiation, we performed a retrospective study to check the relationship between miR-30a*, miR-30e* expression and histologic grade in OPSC patients. A 50-sample training set (type I, 16; type II, 34) was used to identify miR-30a* or miR-30e* expression pattern that could predict the histological differentiation through the analysis of leave-one-out cross predictions. Using a cutoff of 9.550466 and 11.82391 with the highest Youden’s index for miR-30a* and miR-30e*, respectively, we accurately predicted the grade, and the accuracy, sensitivity and specificity are 80.0, 85.4 and 79.5% for miR-30a* and 86.0, 79.2 and 92.2% for miR-30e*, respectively (Fig. 5A and B). Mann-Whitney U tests for statistical significance (p<0.001 for all groups) demonstrated the capacity of the predictor to distinguish type I OPSC patients from type II OPSC patients. The mean AUC values (area under ROC curve) of miR-30a* and miR-30e* are 0.889 and 0.895, respectively (Fig. 5C and D).

To further validate the predictive value of prognostic biomarkers for miR-30a* and miR-30e* expressions in clinical outcome, we performed Kaplan-Meier survival analysis for OPSC patients who were divided into two sub-sets according to high and low expression level of the miR-30a* and miR-30e* (Fig. 5E and F). Diagnosis is based on the analysis of above ROC curves. Kaplan-Meier survival analysis indicated that low expression of miR-30a* and miR-30e* was significantly associated with shorter overall survival of the OPSC patients as compared with the high miR-30a* and miR-30e* expression groups, respectively, log-rank p<0.01 for all.

Taken together, these results indicate that the expression levels of miR-30a* and miR-30e* could serve as novel predictors and prognostic biomarkers for OPSC patient response to histologic grade and survival.

Discussion

Histological grade has already been recognized as a very important prognostic factor for ovarian serous carcinoma (5,6). However, there are still several unresolved issues concerning the grading of this disease in which there is no agreement regarding the designation with well, moderate, poor differentiation vs. I, II, III vs. 1,2,3,4 vs. low and high-grade (5,6). Based on the recent clinicopathological and molecular studies, some researchers proposed a model for grading serous ovarian cancer. In this model, surface epithelial tumors are divided into a two-tier system for histologic grade that is based primarily on the assessment of nuclear atypia (uniformity vs. pleomorphism) in the worst area of the tumor (1,5,7). Type I tumors are mainly low-grade and relatively genetically stable. In contrast, high grade serous carcinoma is by far the most common type II ovarian cancer and highly aggressive. Type I tumors are associated with distinct molecular changes that are rarely found in type II tumors. Low-grade serous carcinomas typically pursue an indolent course that may last more than 20 years (1,17,18). This contrasts with conventional high-grade serous carcinoma that accounts for approximately 75% of ovarian cancer but is responsible for most of the deaths (6,19) and almost always have progressed to advanced stage at diagnosis, when current available therapies are seldom curative (7,9). Women in our study had 77% high-grade, whereas only 23% had low-grade. This is in line with the other studies examining survival of ovarian serous carcinomas using the two-tier system (6). In our investigation, we found that women with high-grade had a significantly increased risk of ovarian cancer compared with women with low-grade (Table II). Similar results were found in other studies (5,6).

Through miRNA microarray and targets prediction analysis, 23 miRNAs were found to be highly differentially expressed in tumors from type I vs. type II OPSC patients. miR-30a* and miR-30e* were the top 2 miRNAs that showed significant differential expression in OPSC patients between the type I and II, and were remarkably downregulated in the latter group, suggesting that these miRNAs are involved in differentiation of serous ovarian cancer. To further understand the mechanisms and to investigate the functions of miRNAs in the development of ovarian pathological differentiation, miRNA target prediction and pathway analysis were done. ATF3 and MYC were indicated as potential co-targets of both miRNAs, and they were validated as significantly upregulated in type II OPSC patients.

ATF3 is a member of the ATF/CREB family of transcription factors (4), as an oncogene, ATF3 contributes to the successful propagation of human cancer (4,2124), and promotes metastasis, cell adhesion and invasion, cell proliferation, apoptosis and cell differentiation (2527) (Fig. 6). ATF3 plays a complex role in tumor progression, and it is possible that some of the apparent contradictions in terms of the function of the ATF3 gene arise at least in part due to the difference in the cellular context (25). Similarly to ATF3, MYC levels can be activated in a wide variety of human hematological malignancies and solid tumors (28). Deregulation of MYC contributes to the genesis of a wide spectrum of human tumors through many biological activities including cell growth and division, cell cycling, cell differentiation, apoptosis and cell adhesion and motility (28) (Fig. 6). The most common MYC aberration in solid tumors is gene amplification. In ovarian cancer, MYC over-expression is observed with a frequency of around 40% (28). Importantly, MYC inactivation resulted in tumor regression and/or differentiation in several experimental systems (2831). Jain et al found that even transient inactivation of MYC was sufficient to achieve tumor regression and cell differentiation (32). The above-mentioned studies revealed that ATF3 and MYC are often associated with aggressive behavior and poor differentiation, especially in human cancers (28). These results are in good agreement with our findings and point toward a regulating differentiation function of the miR-30a* and miR-30e* genes.

To further validate this hypothesis, we investigated the leave-one-out cross predictions of OPSC histological grade stratified by expression levels of miR-30a* and miR-30e*, respectively. By checking and following-up on the patient’s medical records, we unexpectedly found that miR-30a* and miR-30e* can predict histological grade with accuracy of up to 80.0 and 86.0%, and AUC values are 0.889 and 0.895, respectively. Kaplan-Meier survival analysis indicated that low expression of miR-30a* and miR-30e* were all significantly associated with shorter overall survival of the OPSC patients. These findings strongly suggested that miR-30a* and miR-30e* can be used as biomarkers to tailor histological grade before starting the regimen, and they have important roles in ovarian cancer differentiation resulting in poorer prognosis.

To our knowledge, this study is the first to indicate and validate the roles and significance of miR-30a* and miR-30e* in histologic differentiation of ovarian papillary serous carcinoma. As most current cancer therapies are highly toxic and often non-specific, recently, a potentially less toxic approach, termed ‘differentiation therapy’, to treating this prevalent disease is raised. This approach employs agents to modify cancer cell differentiation, which on appropriate treatment, results in tumor re-programming and a concomitant loss in proliferative capacity and induction of terminal differentiation or apoptosis (33). We hope our research can improve understanding of molecular mechanisms of EOC development and progression, especially in histologic differentiation, so that we can provide improved diagnostic, prognostic and therapeutic approaches to individual patients, especially in differentiation therapy to high-grade OPSC cases.

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June-2014
Volume 44 Issue 6

Print ISSN: 1019-6439
Online ISSN:1791-2423

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Spandidos Publications style
Wang Y, Li L, Qu Z, Li R, Bi T, Jiang J and Zhao H: The expression of miR-30a* and miR-30e* is associated with a dualistic model for grading ovarian papillary serious carcinoma. Int J Oncol 44: 1904-1914, 2014
APA
Wang, Y., Li, L., Qu, Z., Li, R., Bi, T., Jiang, J., & Zhao, H. (2014). The expression of miR-30a* and miR-30e* is associated with a dualistic model for grading ovarian papillary serious carcinoma. International Journal of Oncology, 44, 1904-1914. https://doi.org/10.3892/ijo.2014.2359
MLA
Wang, Y., Li, L., Qu, Z., Li, R., Bi, T., Jiang, J., Zhao, H."The expression of miR-30a* and miR-30e* is associated with a dualistic model for grading ovarian papillary serious carcinoma". International Journal of Oncology 44.6 (2014): 1904-1914.
Chicago
Wang, Y., Li, L., Qu, Z., Li, R., Bi, T., Jiang, J., Zhao, H."The expression of miR-30a* and miR-30e* is associated with a dualistic model for grading ovarian papillary serious carcinoma". International Journal of Oncology 44, no. 6 (2014): 1904-1914. https://doi.org/10.3892/ijo.2014.2359